Embodiments of the invention relate generally to an apparatus and method for detector threshold calibration.
Diagnostics devices typically comprise x-ray systems, magnetic resonance (MR) systems, ultrasound systems, computed tomography (CT) systems, positron emission tomography (PET) systems, and other types of imaging systems. Typically, in CT imaging systems, an x-ray source emits a fan-shaped beam toward a subject or object, such as a patient or a piece of luggage. Hereinafter, the terms “subject” and “object” shall include anything capable of being imaged. The beam, after being attenuated by the subject, impinges upon an array of radiation detectors. The intensity of the attenuated beam radiation received at the detector array is typically dependent upon the attenuation of the x-ray beam by the subject. Each detector element of the detector array produces a separate electrical signal indicative of the attenuated beam received by each detector element. The electrical signals are transmitted to a data processing system for analysis which ultimately produces an image.
Generally, the x-ray source and the detector array are rotated about the gantry opening within an imaging plane and around the subject. X-ray sources typically include x-ray tubes, which emit the x-ray beam at a focal point. X-ray detectors typically include a collimator for collimating x-ray beams received at the detector, a scintillator for converting x-rays to light energy adjacent the collimator, and photodiodes for receiving the light energy from the adjacent scintillator. However, a scintillator/photodiode typically does not provide an energy discrimination (ED) capability, or an ability to distinguish energy level of photons.
As such, recent advances in CT imaging systems include an energy discriminating CT imaging system that may be referred to as an EDCT imaging system. Energy sensitive detectors are used such that each x-ray photon reaching the detector is recorded with its photon energy.
The direct conversion semiconductor detectors allow acquisition of multiple energy bins simultaneously from single acquisition with a single x-ray tube spectrum. EDCT provides energy discrimination and material characterization. For example the system derives the behavior at any other energy based on the signal from two regions of photon energy in the spectrum: the low-energy and the high-energy portions of the incident x-ray spectrum. In an energy region of medical CT, two physical processes dominate the x-ray attenuation: (1) Compton scatter and the (2) photoelectric effect. The detected signals from two energy regions provide sufficient information to resolve the energy dependence of the material being imaged. Furthermore, detected signals from the two energy regions provide sufficient information to determine the relative composition of an object composed of two materials.
A conventional basis material decomposition (BMD) algorithm is based on the concept that in the energy region for medical CT, x-ray attenuation of a material can be represented by a proper density mix of two other materials, referred to as the basis materials. Based on the projections acquired at the two incident x-ray spectra, the BMD algorithm computes two sets of new projections, corresponding to two new CT images that each represents the equivalent density of one of the basis materials. Since BMD contains information regarding density mix of the two basis materials, these images are approximately free of beam-hardening artifacts. An operator can choose the basis material to target a certain material of interest, for example, to get virtually unenhanced image (VUE).
Developments in biotechnology show promise for contrast agents that target specific organs and/or diseases. These contrast agents can be designed to have high-Z elements with a K-edge above 50 keV.
A K-edge indicates a sudden increase in the attenuation coefficient of photons occurring at a photon energy just above the binding energy of the K shell electron of the atoms interacting with the photons. The sudden increase in attenuation is due to photoelectric absorption of the photons. For this interaction to occur, the photons have more energy than the binding energy of the K shell electrons. A photon having an energy just above the binding energy of the electron is therefore more likely to be absorbed than a photon having an energy just below this binding energy. A general term for the phenomenon is absorption edge.
Systems with K-edge contrast materials and/or agents do not fit into the conventional BMD model. The conventional BMD is directed to non K-edge materials. In addition, the conventional BMD cannot account for the K-edge effect of high Z or high atomic number materials such as iodine (I), barium (Ba), tungsten (W), gadolinium (Gd), and xenon (Xe) if the K-edge of the material lies in the active energy region of the incident x-ray spectrum. A design for resolving K-edge contrast agents has employed monochromatic x-ray beams with which the K-edge material can be resolved by imaging the object at photon energies slightly below and slightly above the K-edge, but prevents integration of monochromatic sources with sufficient x-ray flux into a rotating gantry and so limits the application from use as a practical monochromatic x-ray source in medical CT scanners. An exemplary K-edge material comprises a K-edge within an x-ray spectrum employed for a given, selected, and/or particular application. An exemplary non K-edge material may comprise no K-edge, or may comprise a K-edge that is outside the x-ray spectrum for such an application. For example, iodine comprises a K-edge at approximately 33.2 keV. Iodine does comprise a K-edge material in an exemplary low kVp system where the x-ray spectrum covers approximately 20 keV to approximately 50 keV. In another example, iodine would not be considered a K-edge material in a system where the x-ray spectrum starts from approximately 40 keV.
While conventional CT scanners provide Hounsfield unit images that display accurate maps of body density, but limited tissue and material-specific information, spectral CT performs scans with two or more spectra simultaneously to enable material decomposition and quantification. Two spectra (i.e., dual energy CT), are enough to map natural human body composites. However, as stated, more than two spectra are needed for K-edge detection, which make systems using different x-ray spectra not feasible for K-edge detection. In other words K-edge imaging is feasible only with energy sensitive detectors. Moreover, full material specificity is enabled with K-edge materials because no other human tissue has a sudden increase in attenuation in the relevant energy range, enabling improved material characterization. Potential applications of K-edge imaging may allow tagging and detection of cancer and/or vulnerable plaque.
In one technique, photon-counting enables improved energy discrimination, which can benefit from k-edge imaging. Typically, photon-counting is implemented by setting energy thresholds for various bins. That is, multiple bins may be established that are bounded by energy levels, and a number of photon counts occurring in each bin may be used in an imaging application to generate an image. However, different bin setups result in different image quality, material differentiation, and noise. More particularly, spectral imaging data obtained having bins defined non-optimally can lead to a needlessly high level of noise in the final images.
Therefore, it would be desirable to have a data acquisition system for radiation detectors that can optimize threshold positioning in a photon counting application.